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The A00-255 exam has a reputation for tripping up even experienced professionals, and the SASInstitute SAS Predictive Modeling Using SAS Enterprise Miner 14 blueprint keeps getting broader. Rather than guessing what matters, work through the 87 practice questions 2Pass4sure has built around the current exam and walk in knowing the format cold.
SASInstitute A00-255 Exam Overview:
| Certification Vendor: | SASInstitute |
|---|---|
| Exam Name: | SAS Predictive Modeling Using SAS Enterprise Miner 14 |
| Exam Number: | A00-255 |
| Certificate Validity Period: | Valid indefinitely once earned |
| Exam Duration: | 165 minutes |
| Available Languages: | English |
| Related Certifications: | SAS Certified Advanced Analytics Professional |
| Exam Format: | Performance-based, Short answer, Multiple choice |
| Real Exam Qty: | 55–60 |
| Passing Score: | 725 (scale 200–1000) |
| Exam Price: | $250 USD |
| Recommended Training: | SAS Enterprise Miner Training Courses |
| Exam Registration: | SAS Certification Registration Pearson VUE Registration |
| Sample Questions: | DOWNLOAD DEMO |
| Exam Way: | Online proctored or onsite at Pearson VUE test centers |
| Pre Condition: | Recommended: experience with SAS Enterprise Miner, data mining and predictive modeling concepts; no mandatory prerequisites |
| Official Syllabus URL: | https://www.sas.com/en_us/certification/credentials/advanced-analytics/predictive-modeler-14.html |
SASInstitute A00-255 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Data Sources | 20–25% | - Create data sources from SAS tables - Explore and assess data sources - Modify and prepare source data for modeling |
| Pattern Analysis | 10–15% | - Interpret pattern discovery results - Identify clusters and segments |
| Building Predictive Models | 35–40% | - Build models using decision trees - Build models using neural networks - Understand predictive modeling concepts - Build models using regression techniques |
| Predictive Model Assessment and Implementation | 25–30% | - Adjust for oversampling and sampling methods - Score and deploy models - Evaluate performance via profit/loss and comparison - Apply appropriate fit statistics |
SASInstitute A00-255 Exam: Everything You Wanted to Ask
The A00-255 exam is the official SASInstitute exam for SASInstitute SAS Predictive Modeling Using SAS Enterprise Miner 14. Passing it earns you the SAS Certified Predictive Modeler Using SAS Enterprise Miner 14 credential, which sits at the Professional level. It is also connected to SAS Certified Advanced Analytics Professional, so what you learn carries over if you plan to pursue those paths as well. Employers treat the certification as verified proof of skill, which is why structured preparation with 2Pass4sure's practice questions pays off.
The A00-255 exam contains 55–60 questions, and the time limit is 165 minutes. Translate that into a pacing plan before exam day: know roughly how long you can afford per item, flag anything that stalls you, and circle back at the end instead of burning minutes. Two or three full timed sessions in 2Pass4sure's test engine will teach you that rhythm far better than untimed reading ever will.
The passing score for the A00-255 exam is 725 (scale 200–1000), and the official registration fee is $250 USD. Remember that a failed attempt means paying that fee again in full for a retake, so treat self-assessment as part of the budget: run 2Pass4sure's practice questions under timed conditions and only book your seat once your scores sit comfortably above the passing bar.
Recommended: experience with SAS Enterprise Miner, data mining and predictive modeling concepts; no mandatory prerequisites Eligibility details can change, so before you register, confirm the current requirements on the official exam page: https://www.sas.com/en_us/certification/credentials/advanced-analytics/predictive-modeler-14.html.
You can book the A00-255 exam through the official registration channels below:
Exam delivery method: Online proctored or onsite at Pearson VUE test centers.
SASInstitute points candidates to the following official training options:
Once the coursework has built your foundation, the fastest way to turn theory into exam readiness is drilling with 2Pass4sure's 87 practice questions for the SASInstitute SAS Predictive Modeling Using SAS Enterprise Miner 14 exam.
Yes. 2Pass4sure offers a free PDF demo of the SASInstitute SAS Predictive Modeling Using SAS Enterprise Miner 14 practice questions on the samples page, so you can judge the format and quality yourself before paying anything. Every purchase also includes 365 days of free updates, and after the product expires you can extend the update service at a 50% discount from within your member zone.
If you take the corresponding exam within 60 days of purchase and do not pass, 2Pass4sure backs you with a 100% money-back guarantee. To claim it, submit a scanned copy of your exam enrollment slip together with your official Score Report PDF within 2 days of the exam, and the refund is processed within 7 days. The guarantee does not apply to attempts made within the first 3 days after purchase, to products downloaded without actually sitting the exam, or to free materials and expired orders, and the candidate name must match the payer's name. If you would rather have study material than money, you can instead exchange for two additional exam products of equal value, free of charge, while keeping the update service on your original purchase. Delivery itself is instant: your download is available right after payment and a copy reaches your mailbox within one minute — if nothing arrives within 2 hours, contact customer service. You may install the product on as many computers as you need.
The official SASInstitute SAS Predictive Modeling Using SAS Enterprise Miner 14 blueprint is organized into 4 domains. The leading areas are:
- Data Sources — 20–25% of the exam
- Building Predictive Models — 35–40% of the exam
- Pattern Analysis — 10–15% of the exam
For the complete domain-by-domain breakdown with every subtopic, see the Exam Topics outline above.
SASInstitute SAS Predictive Modeling Using SAS Enterprise Miner 14 Sample Questions:
Perform these tasks in SAS Enterprise Miner:
* Continue to use the same diagram. Define and create the data set CREDIT_SCORE for scoring. The variables (their roles and measurement levels) in the CREDIT_SCORE data should be set as identical to those in the CREDIT dat a. The only exception is that the scoring data does not have a TARGET variable.
* Find the best model out of Decision Tree, Decision Tree (3-way), Regression, and Neural Network as defined by each of the four model's overall performance in the validation data measured by average squared error. Now, use this best model to score the CREDIT_SCORE data.
CREDIT SCORE:
The distribution of the predicted probabilities of TARGET=0 in the scoring data is approximately which of the following?
Response:
- A. left skewed
- B. normal
- C. bimodal
- D. right skewed
Correct Answer: A 🗳️
For the variable InqCnt06, replace all values over 10.1 with the value 10. How many values are replaced?
Response:
- A. 200 or higher
- B. 150-199
- C. 0-99
- D. 100-149
Correct Answer: D 🗳️
Transformation of input variables to make their distributions more symmetric will likely have what impact in a logistic regression?
Select one:
Response:
- A. increase the performance of logistic regression
- B. create convergence problems in maximum likelihood estimation
- C. neither increase nor decrease the performance of logistic regression
- D. decrease the performance of logistic regression
Correct Answer: A 🗳️
Perform these tasks in SAS Enterprise Miner:
- Add a Decision Tree node after the Impute node with TARGET as the dependent variable and all other input variables as independent variables (main effects only). Configure the decision tree to use 1 for Number of Surrogate Rules and Largest for Method in Subtree. Do not change any other property of the Decision Tree node.
- Add another Neural Network node after the decision tree with TARGET as the dependent variable and all other input variables as independent variables (main effects only). Configure the Neural Network model to use Average Error for Model Selection Criterion. Do not change any other property for the Neural Network node. Run the process flow.
Which of the following variables was used in the decision tree model?
Response:
- A. TLDel90Cnt24
- B. IMP_TLSatCnt
- C. TLDel3060Cnt24
- D. InqFinanceCnt24.
Correct Answer: C 🗳️
A multilayer perceptron neural network is using three interval inputs to model one interval target (outcome). The neural network has ten hidden units and one hidden layer. How many weights, including biases are being estimated?
You may use a calculator for this question. On the certification exam, an on-screen calculator is provided for you.
Select one:
Response:
- A. 41
- B. 50
- C. 40
- D. 51
Correct Answer: D 🗳️
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